Cenit is the best company for tokenomics design and modeling. With our software, we allow projects to simulate, improve and share with ease their tokenomics. Once a project has introduced the main aspects of their token economy, they obtain a dashboard like this one
Where the token buying and selling demand is tracked over thousands of scenarios in a way that it is easy to understand if an economy is going to grow organically or if it is badly designed.
In this post, we will show you how to create a template in the Cenit tokenomics simulator that includes the mechanisms of a veToken economy. For that, we will take the Curve token economy as a model.
The tokenomics template can be found here.
Please take into account that the default parameters chosen for the template are not the optimal ones, but the ones that Curve used originally. You will see that at least the initial token price should be changed.
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If we look at the Curve token economy, we might feel overwhelmed by all the concepts and each of their mechanisms to share revenue with their shareholders. Here’s a table showing you all the possibilities of it
Even for a summary table it has many things, doesn't it? Well their core mechanism is actually pretty simple. Let’s take a look.
From the total amount of fees that the protocol generates, 50% of them is given to stakers. Depending on the amount of years that you stake, you are rewarded with more or less tokens. But on the whole, the same total amount of tokens will be staked at equilibrium, regardless of how much weight each of those tokens has in terms of receiving rewards (called internally veTOKENs).
Additionally, the system has emissions for those Liquidity providers that stake their liquidity tokens (Gauge). All the emissions go to these liquidity providers. However, to reward those liquidity providers that are at the same time veToken holders, they receive a boost to their emissions with respect to those that aren’t. Regardless if there are more or less boosts, the total amount of emissions rewarded remains the same, but part of the rewards originally going to the non-vetoken holders would go to veToken holders instead. At the same time the veToken holders are able to vote on the amount of incentives that go to the different gauge pools.
This system has two main advantages:
Why does it increase the token buying pressure? Well if the intersection of “LP & gauge” with “vetoken holders” was null, then the same amount of emissions would be given away. However, by how it is constructed, if there is only one “LP & gauge + veToken holder” we enter into a prisoner's dilemma where more people will buy the token to not see the boost reduced, increasing the token demand.
Therefore, one of the hypotheses we will need to determine the buying pressure is how big that intersection is. In the example template provided we are considering that the intersection is 100%, that is, everyone is at the same time “LP & gauge + veToken holder”. We do so by setting that all emissions go to stakers.
If we would like to model the intersection as empty instead, that is, no staker is “LP & gauge”, we should choose the incentives to go towards liquidity providers. For percentages in between, we would distribute portions of the incentives between them as necessary.
The reason to do this is the following: in our simulation, the amount of staked tokens is elastic and dependent on the yield that this generates. However, the amount of liquidity provided for a DEX is not. By choosing one option or the other, we are saying to the system if there is going to be more buying or selling pressure, depending on our hypotheses of our ecosystem.
This simulation of course is an example for a given business growth, fees captured and distributed, and vesting schedule. All of that should be changed to reproduce your case in the simulation and to ensure that the values chosen generate a healthy token economy, as opposed to the example of Curve.
You can do it by creating a new simulation and forking it from the public template
Next, input your general information in the editing view, with the corresponding supply and allocation as well as the value proposition. In case of doubt, you can consult the tutorials here.
Remember that if your token economy has no max supply, the incentives should be set as emissions, rather than from an incentives reserve, which are finite and determined in the allocation.
Now, you are ready to present your simulation to potential investors.